168 search results - page 16 / 34 » Boosting ridge regression |
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
JMLR
2010
13 years 2 months ago
2010
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...
NIPS
2003
13 years 9 months ago
2003
Margin maximizing properties play an important role in the analysis of classi£cation models, such as boosting and support vector machines. Margin maximization is theoretically in...
WSC
2004
13 years 9 months ago
2004
In many practical applications of simulation it is desirable to optimize the levels of integer or binary variables that are inputs for the simulation model. In these cases, the ob...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...